Efficacy of the California Bureau of Land
Management Community Assistance and
­Hazardous Fuels Programs
David J. Ganz1, David S. Saah2, Matthew A. Wilson2, and Austin Troy2
Abstract—This study provides a framework for assessing the social and environmental benefits and public education outcomes associated with the U.S. Department of
the Interior, Bureau of Land Management’s Community Assistance and Hazardous
Fuel Programs in California. Evaluations of fire hazard mitigation programs tend to
focus primarily on the number of acres treated and treatment costs associated with
mitigation without adequately assessing the benefits of these treatments. While some
evaluations account for the value of protected structures or the avoided costs of suppression, few account for the ecosystem service value of protected natural capital.
Examples include the water purification and flood abatement functions of wetlands,
the hydrologic regulation functions of forests, and the recreational value of various
natural landscapes. The total economic value approach to environmental assessment
used in this study includes both the market-based and nonmarket values that are at
risk from wildfire, particularly ecosystem goods and services. Using a decision support
methodology, the data allows the BLM to more effectively quantify and account for
the social and environmental benefits derived from fire mitigation treatments. Suggestions are provided for how this approach could effectively be scaled up and used
at a national, regional, or Statewide level to analyze the efficacy of all BLM programs.
Although this approach is currently compatible with BLM current reporting system, the
assessment provides recommendations on how to augment the evaluation system so
that future program elements or “system” elements that enable (or prevent) communities to take part in raising awareness and taking action for themselves are evaluated
at the broader BLM program level for the Community Assistance and Hazardous Fuel
Programs in California.
Introduction
Not all fire is harmful, and it is important to differentiate between harmful and beneficial fires (Ganz and Moore 2002). Federal fire policy has been
significantly modified since 1995 to recognize and embrace the role of fire
as an essential ecological process (USDA 1995; USDI–USDA 1995; NWCG
2001). The value of ecosystem goods and services should be recognized when
considering the positive and negative effects of fire on a landscape. Traditionally, economic assessment methodologies such as Cost-Benefit Analysis have
not accounted for the value of many ecosystem services because the tools and
techniques to evaluate ecological goods and services in a cost-effective manner were not widely available (EPA 2000; National Research Council 2004).
When tradeoffs are made between alternative land use and fire management
decisions, the best available information is needed to avoid systematic biases
in the resulting decision.
USDA Forest Service Proceedings RMRS-P-46CD. 2007. In: Butler, Bret W.; Cook, Wayne,
comps. 2007. The fire ­environment—
innovations, management, and ­policy;
conference proceedings. 26-30 March
2 0 0 7; D e s t i n , F L . P ro cee d i ng s
R MRS-P-46CD. Fort Collins, CO:
U. S. Department of ­ Agriculture,
Forest Ser v ice, Rock y Mou nta i n
Research Station. 662 p. CD-ROM.
1 Fire Scientist, TSS Consultants,
Oakland, CA. Dganz@tssconsultants.
com.
2 Landscape Ecologist, Economist, and GIS
Analyst, respectively, Spatial Informatics
Group, LLC, San Leandro, CA.
585
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
If hidden costs or benefits are not fully accounted for, people will tend to
make uninformed choices leading to inefficient outcomes. For example, as
witnessed in the Katrina hurricane, the valuation literature has long shown
that offshore barrier islands and near shore saltwater wetlands in the Gulf
Coast region do tend to provide significant benefits to coastal communities
in the form of alleviating flooding and hurricane storm surge (Farber 1987).
Yet, when these ecological benefits are not adequately quantified and incorporated into short-term land use development decisions, critical information
is left outside of the market calculus and inefficiencies arise with sometimes
disastrous results. The same quantification needs to be applied when evaluating the significant benefits to communities living in a fire adapted ecosystem.
While this assessment focuses on the avoided costs of losing these benefits to
an unwanted fire, we recognize that some ecological goods and services may
benefit from periodic low intensity fires. To assist the U.S. Department of
the Interior, Bureau of Land Management (BLM) in California gather such
knowledge, we have developed a conservative, baseline ecological-economic
assessment of the ecosystem goods and services for three selected counties
in that State. Counties were selected based upon the frequency of BLM
projects, the availability of land cover data, and the landscape heterogeneity
and transferability. Our goal has been to use the best available methods, data
sources, and spatial analysis techniques to generate defensible value estimates
that can then be integrated into better land use planning and environmental
decisionmaking throughout the region.
Study Objectives
This study provides the basis for a quantified assessment of the benefits,
cost effectiveness as related to National Fire Plan (NFP) funded projects
administered by the California BLM. The projects evaluated cover those
implemented during the 2002 through 2004 study period. Primary objectives of the study are:
• Quantification of the economic values associated with the Community
Assistance and Hazardous Fuels Programs (HFP) in three counties that
are representative of California’s heterogeneous landscapes.
• Providing a framework and analysis of which BLM fuel reduction projects offer the highest return on the investment when considering the
ecosystem goods and services included as part of the HFP.
The assessment differs from previous ones in that it takes into consideration both the market-based and nonmarket values likely to be impacted by
a catastrophic fire. Specifically, it provides a first-order baseline estimate of
the ecosystem goods and services provide by California’s natural landscapes
that might be threatened by catastrophic fire. Using a decision support methodology developed by Spatial Informatics Group LLC, the NaturalAssets™
Information System, the study presents data that will allow the BLM to more
effectively quantify and account for the social and environmental benefits
derived from fire mitigation treatments.
Study Site Selection
Study sites were chosen by first generating a query map of the concentrations of community assistance grants, and fuels projects funded by the BLM
and the Rural Fire Assistance Program (RFA) from 2002 through 2004.
USDA Forest Service Proceedings RMRS-P-46CD. 2007. 586
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
A density analysis map (fig. 1) was created by the BLM with data generated
from the National Fire Plan Operations and Reporting System (NFPORS).
The purpose of this first level of analysis was to determine those locations in
California that have been targeted for receiving the most funding through
these Federal programs; three counties were chosen that had high concentrations of grant recipients. The three counties selected for performing the
NaturalAssets™ Information System evaluation were Napa, Humboldt, and
San Bernardino. They were selected because:
• These counties represent a good cross section of vegetative communities,
latitude, and development patterns.
• All three have significant BLM lands within their boundaries.
• All three counties have a diverse number of land cover types and hazardous fuel treatments.
• All three counties are covered by the 1997 to 2001 California Land Cover
Mapping and Monitoring Program.
Figure 1—Density analysis of BLM funded projects in California (adapted from BLM 2004).
The density analysis was conducted by BLM using the following data (in a point format):
2002 to 2004 Fuels Treatments (NRPORS), 2002 to 2004 Rural Fire Assistance Grants, 2002 to
2004 Community Assistance Activities only from the following counties: Humboldt, Butte,
Nevada, Napa, Madera, Kern, Los Angeles, San Bernardino, and Orange.
USDA Forest Service Proceedings RMRS-P-46CD. 2007.
587
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
We also provided the BLM with two case studies: the town of Petrolia in
Humboldt County and Morongo Valley in San Bernardino County (fig. 2).
These two case studies are used to compare the costs of treatment to the
estimated benefits from those treatments, including both protected structures and Ecosystem Service Valuations (ESVs). Morongo Valley is a highly
developed part of San Bernardino County while Petrolia is in a rural part of
Humboldt County. Both of these communities are in the wildland urban
interface with Petrolia listed as a Community at Risk and Morongo Valley
listed as a Community of Interest.
Figure 2— Case study locations include Napa,
Humboldt, and San Bernardino Counties.
Methods
Economic valuation can help to ensure that ecosystem services that are not
traded in markets and do not have market prices receive explicit treatment
in economic assessments. Our goal is not to “create” values for ecosystems.
Rather, our purpose is to generate a conservative baseline estimate of the
values that people already hold with respect to these ecosystems through
an assessment of the best available literature. Such information will in turn
assist in our assessments of the benefits provided by community assistance
and hazardous fuels programs in California. This approach is consistent with
that being taken in the international Millennium Ecosystem Assessment,
which focuses international policymakers’ attention on the contributions of
ecosystems to human wellbeing (Millennium Ecosystem Assessment 2003;
USDA Forest Service Proceedings RMRS-P-46CD. 2007. 588
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
Argady and others 2005). Due to the lack of credible metrics for evaluating
the effectiveness of the BLM projects, we have made a series of assumptions
for this study including:
• Hazardous fuel treatments, irrespective of size, will have an impact on
reducing the fire hazard on a landscape scale. Although the focus of
this assessment is not to model (spatially or temporally) how much of
an impact these treatments might have on fire behavior, there is credible research to indicate that strategically placed treatments can change
fire behavior (Finney 2001; Knapp and others 2004). We assume that
all BLM funded hazardous fuels projects have a beneficial impact on
protecting market and nonmarket assets regardless of the probability of
burning or the level of changes to fire behavior.
• Communities value their structures more than any other market asset.
The research to date on community perceptions of fire support this
assumption (Hodgson 1994; Winter and Fried 2000; Everett 2002).
As far as generating monetary values for marketable assets, this assessment focuses on parcels and the improvement values (generated from
the Grand list) and not other market assets. While the market value of
standing timber is clearly high in Humboldt County, we chose not to
attempt to quantify it due to the lack of data on forest accessibility, size,
and age structure.
• Environmental aesthetics and recreational opportunities are important
services provided by forests in the urban/wildland interface. The natural landscape in and around communities has amenity and recreational
values that tend to be quite high in California. In California’s Sierran
foothills, for example, Hodgson (1994) did a survey of residences and
found that one in five respondents considered protection of the landscape
more important than the protection of structures. Californians value
their natural landscape and are willing to pay for the costs associated
with living in a fire-prone area for the other natural amenities that these
surroundings provide.
• There are additional ecosystem goods and services from which local
­California residents benefit even though they may not be as aware of
them. These include flood avoidance, wildlife habitat refugia, and clean
water provision, all of which provide real benefits to society. This assessment includes value estimates for those ecosystem goods and services
that have been quantified in the peer-reviewed literature.
• If hazardous fuel treatments are going to be effective in California, they
need to be coordinated with an outreach effort to raise awareness of
why landscape scale treatments are needed. This is especially important
in California where the environmental assessments (performed under
the National Environmental Protection Act and/or the California Environmental Quality Act) require public input and often turn into legal
battles over whether fuel treatments are appropriate in certain ecological
and socio-political systems. Although it is not within this assessment’s
scope to address or resolve these conflicts, we should be aware that they
exist in the State and contribute to the costs of implementing a hazardous fuel treatment program.
Building on these assumptions, we recognize that the protection of forests from fire damage can generate real benefits to society—benefits that go
beyond the protection of market goods and structural assets. Scenic views,
recreational opportunities, flood control, wildlife habitat protection, sediment retention, and water supply all contribute to the wellbeing of people
USDA Forest Service Proceedings RMRS-P-46CD. 2007.
589
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
and the communities they live in. The challenge is that currently many of the
economic values associated with fire mitigation efforts remain unaccounted
for because they are not easily quantified in conventional policy assessments
or cost-benefit analyses.
Value Transfer of Nonmarket, Nonuse Estimates
One of the primary goals in this the study is to shed light on the nonmarket
economic benefits of ecosystem goods and services associated with the landscapes that are affected by fire hazard mitigation efforts. While a fair amount
of research has been done on the economic value of ecosystem services globally (Costanza and others 1997; Millennium Ecosystem Assessment 2003),
relatively limited peer-reviewed work has been done to estimate the specific
economic values of ecosystem services located in San Bernardino, Napa, and
Humboldt Counties. Because limited empirical ecosystem service valuation
research has been done at the study sites, we were required to “transfer”
values from other sites.
Measuring the use values associated with marketed goods and services simply requires monitoring market data for observable trades; but the nonmarket
values of goods and services are much more difficult to measure (Bingham
and others 1995). When there are no explicit markets for ecosystem goods and
services, more indirect means of assessing economic values must therefore be
used. A subset of economic valuation techniques commonly used to establish
values when market values do not exist are identified in table 1. (This list of
nonmarket valuation techniques is not intended to be all-inclusive. Rather,
it is intended to reveal the breadth of available empirical techniques that
have been and are currently being explored in the field of ecosystem service
valuation.)
Table 1—Conventional nonmarket valuation techniques.
Avoided Cost (AC): services allow society to avoid costs that would have been incurred in the absence of
those services; flood control (barrier islands) avoids property damages, and waste treatment by wetlands
avoids incurred health costs.
Marginal Product Estimation (MP): Service demand is generated in a dynamic modeling environment
using production function (that is, Cobb-Douglas) to estimate value of output in response to
corresponding material input.
Factor Income (FI): services provide for the enhancement of incomes; water quality improvements
increase commercial fisheries harvest and, thus, incomes of fishermen.
Travel Cost (TC): service demand may require travel, whose costs can reflect the implied value of the
service; recreation areas attract distant visitors whose value placed on that area must be at least what they
were willing to pay to travel to it.
Hedonic Pricing (HP): service demand may be reflected in the prices people will pay for associated
goods: For example, housing prices along the shore of pristine freshwater lakes tend to exceed the prices
of inland homes.
Contingent Valuation (CV): service demand may be elicited by posing hypothetical scenarios that
involve some valuation of alternatives; people would be willing to pay for increased water quality in
freshwater lakes and streams.
USDA Forest Service Proceedings RMRS-P-46CD. 2007. 590
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
As the descriptions in table 1 suggest, each nonmarket valuation methodology represented in the NaturalAssets™ information system (NAIS) has
its own strengths and limitations, often limiting its use to a select range of
ecosystem goods and services within a given landscape. For example, the
economic value generated by a naturally functioning ecological system can be
estimated using avoided cost (AC), based on the estimated cost of damages
due to lost services. However, because these estimates are highly sensitive
to market conditions used to estimate costs, they must be used with great
caution. While rigorous and well established in the field, travel cost (TC) is
primarily limited to estimating recreation values, while hedonic pricing (HP)
is used for estimating property values associated with aesthetic qualities of
natural ecosystems. On the other hand, contingent valuation (CV) surveys
are often widely used to estimate the economic value of less tangible services
such as critical wildlife habitat or biodiversity. The challenge with CV and
related methods such as choice modeling is that estimated values are highly
sensitive to the survey format and context of valuation (Heberlein and others 2005).
In this study, the full suite of ecosystem valuation techniques is used to
account for the economic value of goods and services provided by natural
landscapes in San Bernardino, Napa, and Humboldt Counties.
Value transfer by definition involves the adaptation of existing valuation
information or data to new policy contexts with little or no data. (Following
Desvouges and others [1998], the term “value transfer” is used instead of
the more commonly used term “benefit transfer” to reflect the fact that the
transfer method is not restricted to economic benefits, but can also be extended to include the analysis of potential economic costs, as well as welfare
functions more generally.) The transfer involves obtaining an estimate for
the economic value of nonmarket goods or services through the analysis of
a single study, or group of studies, that have been previously carried out to
value similar goods or services. The transfer itself refers to the application
of estimated point values, derived utility functions, and other information
from the original “study site” to a “policy site” (Loomis 1992; Desvousges
and others 1998).
While we accept the fundamental premise that primary valuation research
will always be a “first-best” strategy for gathering information about the
value of ecosystem goods and services (Smith 1992; Downing and Ozuna
1996; Kirchhoff and others 1997), we also recognize that value transfer has
become an increasingly practical way to inform policy decisions when primary
data collection is not feasible due to budget and time constraints, or when
expected payoffs are small (EPA 2000; National Research Council 2004).
In other words, value transfers will always represent a policy-relevant compromise solution. When primary valuation research is not possible or plausible,
then value transfer, as a “second-best” strategy, is important to consider as a
source of meaningful baselines for the evaluation of management and policy
impacts on ecosystem goods and services. However, the real-world alternative is to treat the economic values of ecosystem services as zero; a status quo
solution that, based on the weight of the empirical evidence, will often be
more error prone than value transfer itself.
USDA Forest Service Proceedings RMRS-P-46CD. 2007.
591
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
Ecosystem Service Valuation (ESV) Data
The raw material for the value transfer exercise comes from previously
published studies that empirically measured the economic value of environmental goods and services. Three types of valuation research exist in the
literature today:
• Peer-reviewed journal articles, books and book chapters, proceedings,
and technical reports that use conventional environmental economic
valuation techniques and that are restricted to an analysis of social and
economic values.
• Non peer-reviewed publications that include PhD dissertations, non peerreviewed technical reports and proceedings, as well as raw data available
on the Internet.
• Secondary analysis (for example, meta analysis) of peer-reviewed and/or
non peer-reviewed studies that use both conventional and nonconventional valuation methods.
The critical underlying assumption of NAIS is that the ESVs for ecosystem
goods or services can be inferred with sufficient accuracy from the analysis
of existing nonmarket valuation studies. Clearly, as the level of information
increases within the source literature (in other words, more studies are done),
the accuracy of the value transfer likewise improves. The research team developed a set of explicit decision rules for querying economic results from the
raw data contained in NAIS that would allow us to estimate with sufficient
accuracy the economic value of ecosystem services in San Bernardino, Napa,
and Humboldt Counties. The research team selected valuation studies that
were:
• Peer reviewed and published in recognized journals
• Focused on temperate regions in either North America, Canada, or Europe
• Focused primarily on nonconsumptive use
Using these search criteria, we were able to obtain data from a set of viable
studies (n=84) whose results were then standardized to 2004 U.S. dollar
equivalents per acre to provide a consistent basis for comparison. (All dollar
values are standardized to 2004 using Consumer Price Index tables published
by the U.S. Department of Labor; http://www.bls.gov/cpi/home.htm.)
Because each study may contain more than one estimate of value, the end
result is a collection of valuation data points that are coded by temporal (that
is, time of study), spatial (place where study was done), and methodological
(method used) criteria, thereby allowing the research team to derive a lower
bound and upper bound estimate of dollar values for the study site. For this
study, we were able to generate a total of (n=205) individual point estimates
for reviewed land cover types. Given the aforementioned restrictions and gaps
in the available literature, this approach yields conservative, baseline economic
values for San Bernardino, Napa, and Humboldt Counties.
In sum, the transfer method adopted in this report involves obtaining an
estimate for the value of ecosystem goods or services through the analysis of
peer-reviewed research that has been previously collected and stored in NAIS
in a standardized format so that it can further be augmented with site-specific
GIS data (that is, land cover, socioeconomic characteristics) to ensure reliable
valuation estimates at the study site.
USDA Forest Service Proceedings RMRS-P-46CD. 2007. 592
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
Spatial Analysis Methods
Another principal goal in this study is to link the ESV estimates for ecosystem goods and service to available land cover/land use data in San Bernardino,
Napa, and Humboldt Counties. Thanks to the increased ease of using GIS
and the availability of land cover data sets derived from satellite images, ecological and geographic entities can more easily be attributed with ecosystem
services and the values they provide to people (Wilson and others 2004;
Wilson and Troy 2005). In simplified terms, the technique discussed here
involves combining one land cover layer with another layer representing the
geography to which ecosystem services are aggregated—that is, a watershed.
While the aggregation units themselves are likely to be in vector format, because vector boundaries are most precise, the land cover layer may be either
raster or vector. (The vector data model represents spatial entities with points,
lines and polygons. The raster model uses grid cells to represent quantities or
qualities across space.) Spatial disaggregation increases the contextual specificity of ecosystem value transfer by allowing us to visualize the exact location
of ecologically important landscape elements and overlay them with other
relevant themes for analysis—biogeophysical or socioeconomic. A common
principle in geography is that spatially aggregated measures of geographic
phenomena tend to obscure local patterns of heterogeneity (Openshaw and
others 1987; Fotheringham and others 2000).
Development of Land Cover Typology
Two types of values were spatially mapped for this project: ecosystem
service values and structural improvement values. These require accurate,
high resolution, and categorically meaningful depictions of land cover. Before developing these maps, a land cover typology was created. To do this,
we assessed available data coverages to determine which land cover classes
at what level of categorical precision could be mapped at a usable scale and
with acceptable levels of accuracy. Table 2 shows the resulting typology with
the code name for each cover class, its description and the counties in which
it was present.
Table 2—Land cover typology with applicable counties.
Code
AGR
CON
DSHB
DWLD
EST
FWET
HDW
HEB
MIX
OWLF
RIPF
RW2
RWOG
SHB
SWET
URB
URBG
VIN
WAT
Description
Agriculture Conifer
Desert scrubland
Desert woodland
Estuary and tidal bay
Fresh wetland
Hardwood oak woodland
Herbaceous Mixed hardwood, conifer
Forested areas suitable for spotted owl habitat Riparian forests (50 m buffer)
Redwood-second growth
Redwood-old growth
Shrubs
Salt wetland
Urban and barren Urban green (forest and grass)
Vineyard
Open water
USDA Forest Service Proceedings RMRS-P-46CD. 2007.
Counties
All
All
San Bernardino
San Bernardino
Napa, Humboldt
All
All
All
All
Humboldt
All
Napa, Humboldt
Humboldt
All
Napa, Humboldt
All
All
Napa
All
593
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
Spatially Explicit ESV Calculation Methods
Ecosystem service values were then determined by multiplying areas of
each cover type, in acres, by the dollar per acre ecosystem service value for
that cover type. The economic values used to estimate the values associated
with each ecosystem good or service are drawn from the NAIS ESV data.
The total ESV of a given cover type for a given watershed can thus be determined by adding up the individual, nonsubstitutable ecosystem service values
associated with that cover type. The following formula is used:
n
V(ESk) = ¤ A( LU i ) s V ( ES ki )
i 1
Where A(LUi) = area of land use (i)
and V(ESki) = annual value of ecosystem services (k) for each
land use (i).
Resulting values were estimated for the entire study area using value transfer
methods. Following that, the ESVs were aggregated by county study area,
broken down for each county by land cover, and cross-tabulated for each
study site by (1) land cover and watershed and (2) land cover and zip code.
Assessed structural improvements were also summarized to generate a total
economic value estimate for critical human-modified land uses.
Results
Using the value-transfer search criteria, the research team obtained data
from a set of 84 viable empirical studies, whose results were then standardized
to 2004 U.S. dollar equivalents per acre/per year to provide a consistent basis
for comparison in the tables in this section. (All economic valuation data in
this report are have been standardized to represent total net present values,
not discounted. This allows for the results to be incorporated into forwardlooking scenarios that might weight future costs and benefits differently than
current costs and benefits when summing over time using specific discount
rates; Heal 2004.) The aggregated baseline ESV results for all land cover
types represented within the study area are presented in table 3.
The ESV data in table 3 show the minimum, the maximum, and the average
nonmarket ecosystem service valuation estimates aggregated across all land
cover types contained in the study. (Not all land cover types generated for the
spatial analysis of San Bernardino, Napa, and Humbolt Counties by the Spatial
Informatics Group team could effectively be matched with equivalent ESV
estimates as denoted in table 4.) Clearly, not all land cover types represented
in this report provide benefits to society equally. Rather, consistent with previously published literature (Daily 1997; Wilson and Carpenter 1999), the data
reveal how land cover types in the study area that are associated with water
(wetlands, estuaries, and riparian forest) tend to yield the largest ecosystem
service values per area unit. Also consistent with previous findings, it also
appears that both agricultural systems (in this report, the same ESVs were
assigned to agricultural and vineyard land cover types) and urban greenspace
tend to yield fairly large values per unit of measurement (Pretty and others
2000; Ricketts and others 2004). While nonriparian forest systems tend to be
less valuable per acre unit, there is still a range of variability evidenced among
different forest types, with old growth and spotted owl habitat yielding the
highest values per unit and oak woodland yielding the least.
USDA Forest Service Proceedings RMRS-P-46CD. 2007. 594
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
Table 3—Aggregate ecosystem services for all available land cover types.
Code
AGR
CON
DSHB
DWLD
EST
FWET
HDW
HEB
MIX
OWLF
RIPF
RW2
RWOG
SHB
SWET
URB
URBG
VIN*
WAT
Description
Min $ acre/yr
Agriculture $83.47
Forest-conifer
$32.48
Desert shrub
NA
Desert woodland
NA
Estuary
$1,483.90
Fresh wetland
$1,761.07
Hardwood oak woodland
$61.68
Herbaceous NA
Mixed hardwood, conifer
$34.32
Spotted owl habitat
$100.53
Riparian forest
$122.17
Redwood second growth
$29.89
Redwood old growth
$84.63
Shrubs
NA
Saltwater wetland
$229.18
Urban and barren
NA
Urban green
$602.29
Vineyards
$83.47
Open fresh water
$227.79
Max $ acre/yr
$1,689.04
$999.79
NA
NA
$5,239.01
$9,180.73
$486.84
NA
$1,001.63
$1,113.86
$15,126.99
$997.20
$1,051.94
NA
$8,845.04
NA
$4,289.91
$1,689.04
$13,073.87
Avg $ acre/yr
$887.06
$332.35
NA
NA
$2,386.75
$4,440.73
$177.82
NA
$334.19
$403.86
$3,558.03
$329.76
$384.50
NA
$2,446.06
NA
$2,268.21
$887.06
$2,928.72
*Note: Assumption that AGR and VIN ESVs are equivalent as both are intensively managed and
represent human dominated systems.
Spatially Explicit Ecosystem Service Valuation Results
Building on the ESV data generated with NAIS, the research team was
able to use the spatially explicit ESV calculation methods, to generate ESV
results. Tables 4 and 5 provide summaries of total ESVs by land cover class
and reveal that significant differences exist between the three counties in
the study.
Significant economic benefits clearly accrue to society from forests in
Humboldt County. As the data in table 4 show, forest-related land cover
types account for an overwhelming proportion (almost 80 percent) of total
ESV delivered by naturally functioning ecological systems in the study area.
Thus, while on a per-unit basis, forest land types may tend to provide less
economic value than nonforested systems, the large study area currently under forested cover brings the total economic value associated with forests to
the foreground. After forests, it appears that freshwater wetlands (FWET)
and open water (WAT) provide the next most significant ESVs in the study
area.
In contrast to Humboldt County, forested systems appear to account for
only approximately 30 percent of the total ESV delivered by functioning ecological systems in Napa County. Napa’s open freshwater (WAT) alone in the
form of streams, lakes, and rivers appears to provide a significant economic
benefit to society (31 percent). And as might be expected, both agricultural
land (AGR) and vineyards (VIN) also provide a substantial positive impact
on the economic value associated with ecosystem services in the region
­(approximately 20 percent). For Napa County, the zip codes of high value
(both structural and ESV) are within Napa and St. Helena.
The data in table 6 reveal that similar to Napa County, forested systems
deliver approximately 31 percent of the total ESV delivered by ecological
systems in San Bernardino County. Freshwater wetlands (FWET) account
USDA Forest Service Proceedings RMRS-P-46CD. 2007.
595
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
Table 4—Humboldt County study areas land cover and ESV estimates.
Study area zip codes
Class
AGR
CON
EST
FWET
HDW
HEB
MIX
OWLF
RIPF
RW2
RWOG
SHB
SWET
URB
URBG
WAT
Acres
ESV/acre
Entire county
Total ESV
Acres
ESV/acre
Total ESV
38,973
887
34,571,513
39,380
887
34,932,508
271,121
332
90,107,174
282,303
332
93,823,306
4
2,387
10,085
4
2,387
10,085
23,676
4,441
105,140,399
23,704
4,441
105,261,803
272,587
178
48,471,365
277,209
178
49,293,301
201,869
NA
205,292
NA
628,282
334
647,218
334
209,965,524
216,293,687
221,523
404
89,464,211
221,580
404
89,487,414
117,270
3,558
417,250,658
122,248
3,558
434,960,966
230,466
330
75,998,467
246,197
330
81,185,900
90,604
385
34,837,363
98,005
385
37,682,967
53,085
NA
55,556
NA
1,344
2,446
1,356
2,446
3,287,882
-
3,317,256
41,821
NA
42,944
NA
8,042
2,268
18,239,981
8,043
2,268
18,242,491
17,266
2,929
TOTAL ESV
50,566,177
1,177,910,801
17,655
2,929
TOTAL ESV
51,707,928
1,216,199,612
Known market values
improvement
value of
structures
$4,376,522,485
TOTAL
$5,554,433,286
-
Known market values
improvement
value of
structures
$4,499,321,899
TOTAL
$5,715,521,511
Table 5—Napa County study areas land cover and ESV estimates.
Class
AGR
CON
EST
FWET
HDW
HEB
MIX
RIPF
RW2
SHB
SWET
URB
URBG
VIN*
WAT
Study area zip codes
Acres
ESV/acre
Total ESV
26,265
887
23,298,875
16,891
332
5,613,779
1,110
2,387
2,648,298
4,409
4,441
19,577,352
141,771
178
25,209,687
64,207
11,704
334
3,911,425
16,880
3,558
60,060,503
1,257
330
414,390
113,065
3,438
2,446
8,409,695
18,408
1,808
2,268
4,099,948
35,032
887
31,073,702
29,688
2,929
86,947,804
TOTAL ESV
271,265,459
Known market values
improvement
value of
structures
$10,957,341,955
TOTAL
$11,228,607,414
USDA Forest Service Proceedings RMRS-P-46CD. 2007. Acres
27,700
17,327
1,115
4,412
145,867
66,148
13,619
17,479
1,262
119,967
3,450
18,462
1,808
35,034
29,918
Entire county
ESV/acre
887
332
2,387
4,441
178
334
3,558
330
2,446
2,268
887
2,929
TOTAL ESV
Total ESV
24,571,316
5,758,593
2,661,834
19,592,412
25,938,010
4,551,190
62,189,858
416,315
8,438,390
4,099,948
31,075,280
87,621,444
276,914,591
Known market values
improvement
value of
structures
$11,256,915,849
TOTAL
$11,533,830,440
596
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
Table 6—San Bernardino study areas land cover and ESV estimates.
Class
AGR
CON
DSHB
DWLD
FWET
HDW
HEB
MIX
RIPF
SHB
URB
URBG
WAT
Study area zip codes
Acres ESV/acre
Total ESV
39596.26
$887
$35,124,255
282191.6
$332
$93,786,377
5260821
596696.3
113840.5
$4,441
$505,534,805
37049.87
$178
$6,588,207
34444.69
69668.12
$334
$23,282,391
84104.76
$3,558
$299,247,244
384160.9
441379.6
121.74
$2,268
$276,129
27602.46
$2,929
$80,839,872
TOTAL ESV
$1,044,679,280
Entire county
Acres
ESV/acre
Total ESV
71,762
$35,124,255
$63,657,272
333,674
$93,786,377
$110,896,564
10,189,383
606,121
185,251 $505,534,805
$822,650,494
47,948
$6,588,207
$8,526,125
55,833
85,968
$23,282,391
$28,729,641
93,540 $299,247,244
$332,816,821
482,529
660,011
152
$276,129
$344,531
42,117
$80,839,872
$123,347,887
TOTAL ESV
$1,490,969,334
Known market values
Known market values
improvement
value of
structures
TOTAL
$35,770,650,855
$36,815,330,135
improvement
value of
structures
TOTAL
$68,941,985,365
$70,432,954,699
for the majority of ecosystem service benefits delivered to society (55 percent) —by far the single most important ecosystem type in the study area
from an ecosystem services perspective. Given that desert shrub is the most
predominant land cover type in the county and that no ESVs were estimated
for desert land cover types in this study, we anticipate that fire-related ESVs
would be forthcoming for these critical ecosystem types as this information
is gathered and included in this type of analysis.
An overwhelming proportion of ecosystem service values in Humboldt
County comes from its forests. Humboldt’s relatively large area of forested
cover accounted for nearly 80 percent of total ESV delivery by naturally
functioning ecological systems in the study area. On a per-unit basis, some
forest types provide a lower stream of benefits than many non-forested types,
but the size of forested area in Humboldt County means that ESV benefits
from forests dominate. For instance, the Six Rivers National Forest contributes $293 million in ESV to Humboldt County with an additional $19
million in market values (such as structures). This contribution is primarily
due to its size, and to the dominance of redwood old growth and spotted
owl habitat.
In Napa County, forested systems only accounted for 30 percent of ESVs
delivered by functioning ecological systems. Napa’s open freshwater, in the
form of streams, lakes and rivers, provided 31 percent of measured economic
benefits to society. Both agricultural land and vineyards also provide a substantial positive impact on the economic value associated with ecosystem services
in the region (approximately 20 percent). The communities of Napa (zip codes
94558 and 94559) and Saint Helena (94574) have the highest estimated
quantities of ESVs and structural values within Napa County (fig. 3).
USDA Forest Service Proceedings RMRS-P-46CD. 2007.
597
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
Figure 3—Total estimated ecosystem service valuation by zip code for Napa County study area.
USDA Forest Service Proceedings RMRS-P-46CD. 2007. 598
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
Similar to Napa County, forested systems delivered approximately 31
percent of the total ESVs delivered by ecological systems in San Bernardino
County. From an ecosystem services perspective, freshwater wetlands accounted for the majority (55 percent) of ecosystem service benefits delivered to
society. For instance, the community of Twenty Nine Palms (zip codes 92277
and 92278) has low assessed structural values relative to other communities
in San Bernardino County, but the freshwater resources of this community
yield considerable ESVs compared with the rest of the communities within
this county (fig. 4). Desert shrub is the most predominant land cover type in
San Bernardino County. However, there are two reasons why this land cover
shows few societal benefits in this study. First, this desert-related land cover
type tends not to burn, and second, the value transfer analysis did not yield
any ESV studies that estimated economic values for desert cover types.
Figure 4—Total estimated ecosystem service valuation by zip code for San Bernardino County study area.
Cost Effectiveness of Fire Hazard Mitigation Efforts
In this section, we provide a cost effectiveness framework by which the BLM
fuel hazard mitigation programs can be evaluated relative to their return on
investment and agency management goals. This framework takes into consideration both the capital costs and the avoided losses to ecosystem services
associated with fire mitigation. This will allow the BLM and other agencies
to consider the real losses to ecosystem goods and services that might occur
in the event that such fuel treatments were not implemented. For example, in
Humboldt or Napa Counties, the treatment costs per acre range from $306
USDA Forest Service Proceedings RMRS-P-46CD. 2007.
599
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
to $600/acre but the estimated benefits of fire mitigation are conservatively
between $117 to $4,440/acre (using the lower range average ESV for hardwood oak woodland and higher range average ESV for fresh water wetland).
Regardless of whether the proposed fuel treatment uses prescribed burning
or mechanical treatment (in either of these two counties), the costs per acre
to benefit ratio will be higher when we include the accounting of avoided
losses of ESVs. This application is further explained in two case studies of
Morongo Valley and Petrolia. Using these case studies, we compared the costs
of treatment to the estimated benefits from those treatments, including both
protected structures and ESVs.
An additional analysis was used to evaluate the cost effectiveness of all
projects within these three counties by agency and by treatment. NFPORS
is an interagency system designed to assist field personnel in managing and
reporting accomplishments for work conducted under the National Fire Plan.
As it is spatially explicit, NFPORS allows for the accounting of natural assets
surrounding BLM projects using both artificial boundaries (like zip codes
or parcels) and natural boundaries (watershed boundaries and tributaries).
The NFPORS system also allows us to evaluate the contribution of the BLM
projects to the overall fire mitigation framework within these three counties
and compare their efficiencies with metrics such as per acre treatment costs
and their ESV avoided costs. For instance, in Humboldt County, of all the
money spent by Federal agencies on fuel hazard reduction treatments, BLM
spent 5.6 percent of the total on fire treatments and 29 percent on mechanical treatments. For Humboldt County, the BLM spent $306/acre on fire
treatments and $377/acre on mechanical treatments. In Napa County where
all of the treatments were performed by the BLM, 63 percent of the treatment costs were mechanical (at $600/acre), nearly 4 percent went for fire
treatments, and the remaining 33.5 percent went toward other treatments
(biological and chemical). While these may seem high compared with the
national averages for fire mitigation treatment, they are comparable with other
parts of California. (The Congressional Research Service Report for Congress
on Forest Fires and Forest Health reported a national average of treatment
costs at $250/acre. On the Shasta Trinity National Forest, treatment costs
for slopes <30 percent ranged from $250 to $600/acre and average $400/
acre.) This would indicate that statements made about the transferability of
these three counties generally apply to these treatment costs.
In an area like Humboldt County, where 6,043 acres were treated in a
variety of ways by the four Federal agencies and their local partners, ESVs
are estimated at $1,177,910,801 while structural values are assessed at
$4,376,522,485, for a total accounting within the Humboldt study area zip
codes of $5,554,433,286. Given the modeling assumptions, the net benefit of
performing these treatments and protecting market and nonmarket assets on
the landscape level from wildfire is $2,504/acre in Humboldt County. Using
the same cost effectiveness approach, we can state that the net benefit from
treatments that protect market and nonmarket assets in San Bernardino and
Napa Counties are $4,994/acre and $22,904/acre, respectively. Compared
with the $2,504/acre “avoided costs” of protecting market and nonmarket
assets in Humboldt, we can easily see that there would be a greater net loss to
society resulting from a major wildfire in Napa County. Yet by reviewing the
overall treatment acreages for Napa across all Federal agencies, the numbers
of acres treated are substantially less than Humboldt and San ­Bernardino.
This is probably due to the lack of Federal agency land, the overall socio­political climate for accepting fuel reduction treatments, and the costs of
doing ­business in Napa County.
USDA Forest Service Proceedings RMRS-P-46CD. 2007. 600
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
There is a national tendency to focus on treatment costs and the total number of acres treated. These metrics tend to favor fire mitigation programs in
other Western States where the costs of labor and materials are lower. Over
the past 36 years, the average annual price increase in California has been
8.9 percent. In 2004, the median home price was $523,150 compared with
the national average of $219,000. These housing trends are ­ undoubtedly
contributing to the differences in costs of treatment between the three counties (table 7). Humboldt County, with its dynamically lower housing costs
and the presence of the timber industry, benefits in the presence of a cost
competitive labor force for implementing fuel treatment projects.
Table 7—BLM planned acres, treatment costs, and costs/acre.
County
Treatment
Humboldt
Fire
Mechanical
Napa
San Bernardino
Planned acres
Cost
$/acres
331
1369
101,246
515,946
306
377
Fire
Mechanical
Other
50
158
255
5,625
94,730
50,500
113
600
198
Mechanical
Other
576
20
243,122
10,000
422
500
Source: Table generated from the NFPORS database. Data from 2004-2005
Our geographic disaggregation of ESVs by watershed (fig. 5) and zip
code (fig. 3 and 4) allows us to depict ESV hotspots and assist the BLM in
prioritizing funding to protect those areas with the highest values. From this
analysis, we can compare the overall funds expended within the three counties
and a per acre “avoided costs” using the total market and nonmarket values
and the acres in the zip code study areas. This then allows for the computation of “net benefits per acre” for each study area acre. Although these costs
and benefits are averaged over an entire zip code or watershed unit, in the
case studies presented below, we have a spatial treatment footprint and will
demonstrate the application at the finest scale possible—that is, of evaluating individual projects. From both of these examples, we can see that as the
BLM partners become familiar with GIS, or as the BLM adjusts its grant
tracking system to include spatial footprints, it should be possible to track
costs and benefits of fuel treatments on different slopes and across different
land cover types.
Case Studies
The two specific case studies, Petrolia in Humboldt County and Morongo
Valley in San Bernardino County, are both within the wildland/urban interface
(WUI). The Healthy Forest Restoration Act (HFR A; HR 1904) requires that
50 percent of the funds expended upon HFR A projects are within the WUI
and municipal watersheds surrounding private homes and communities. In this
Act, the WUI is defined as a 1.5 mile radius around communities; however,
communities can define their own WUI by completing a “community fire
USDA Forest Service Proceedings RMRS-P-46CD. 2007.
601
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
Figure 5—Total estimated ecosystem service value by watershed for Humboldt County study area.
USDA Forest Service Proceedings RMRS-P-46CD. 2007. 602
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
plan.” These case study sites were selected because the BLM has created a spatial
foot print for the actual treatment and sphere of influence. An additional 1.5
mile “buffer” was added to each treatment site because of the Healthy Forest
Restoration Act’s call for vegetative buffers to protect communities. (The 1.5
mile buffer is relevant because when National Environmental Protection Act
analysis is required, the study needs to include only the proposed action and
no action alternative for projects within 1.5 miles of an at-risk community or
in the WUI as defined in the Community Wildfire Protection Plan [CWWP].)
The Total Economic Value (TEV) framework discussed in this study is used
to identify and measure both the nonmarket, ecosystem service values and
the market-based value of protected structures (such as homes) associated with
hazardous fuels treatment. When compared with the actual costs of treatment
for mechanical thinning and chipped/biomass utilization in Petrolia and
Morongo Valley, respectively, these data can be used to evaluate the net social
economic benefit associated with treatments on the ground (see table 8).
The Petrolia mechanical thinning project, implemented by the Mattole
Restoration Council was selected as a case study for Humboldt County. The
project is designed to protect Petrolia, a Community at Risk. It covered 85
acres, and as table 8 shows, the direct cost (excluding administrative) was
$332 per acre for a total one-time cost of $28,188.
The Morongo Valley chipping and biomass removal project, implemented
by the Morongo Valley Fire Safe Council, was selected as a case study for
San Bernardino County. The Morongo Valley chipping and biomass removal
portions of the project covered 40 acres and 35 acres, respectively, and were
designed to protect Morongo Valley, a Community of Interest that is spread
over a larger geographic area. The direct cost (excluding administrative) of
this project was $914 per acre for a total of $69,432.
Table 8 data demonstrate, purely from the total economic value perspective, that both fire treatments considered in this case study appear to be cost
effective. When both the nonmarket and market-based values of protected
structures, goods, and services within the 1.5 mile buffer zone are taken into
consideration, there appears to be a net economic benefit for each community.
For instance, in the case of Petrolia, the data show that treatment project costs
Table 8—Cost effectiveness of treatment in two communities.*
Project community
Petrolia
Morongo Valley
Mechanical thinning
85
10,479
Chipped/biomass utilization
76
17,993
$28,188
$332
$69,432
$937
Market value of protected structures $2,073,213
Nonmarket ecosystem service values $4,570,692
Total economic value $6,643,905
$107,494,431
$379,680
$107,874,111
Project type
Acres treated
Total acres within buffer
Project cost
Project costs per acre
Total economic value per acre Net benefit per acre
$634
$302
$5,995
$5,058
* All dollar values are standardized to 2004 equivalents
USDA Forest Service Proceedings RMRS-P-46CD. 2007.
603
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
were $332 per acre, yet the total economic value of market and nonmarket
goods and services within the protected buffer zone yields approximately $634
per acre, resulting in a net benefit of $302 per acre. In the case of Morongo
Valley, while the costs of treatment were somewhat higher at $937 per acre,
the total economic value of the protected area is also considerably higher
resulting in a net benefit of $5,058 per acre (fig. 6).
What the case study data also show is that the source of economic value
differs considerably for each community. In the case of Petrolia, it appears
that nonmarket ecosystem service values contribute approximately twice as
much to the total economic value of the protected buffer as market-based
values. As a result, if one were to leave out the nonmarket component of
total value in the cost-effectiveness estimate, the end result would have been
quite different: the total economic value would have been only $197 per acre,
resulting in a net cost of $135 per acre for treatment. On the other hand, in
Morongo Valley, the market-based value of homes and structures appears to
far outweigh the nonmarket goods and services associated with the protected
buffer zone, so that the net cost effectiveness of treatment would remain the
same regardless of the nonmarket benefits.
With available time and resources, the approach used in this case study
comparison could effectively be expanded to include all communities in
the Hazardous Fuels Program throughout California. Given the nature of
value transferability, the baseline nonmarket valuation information provided
by NAIS could be linked to other land cover types affected by treatment
Figure 6—Morongo Valley case study area in San Bernardino County; assessed value of structures
by parcel versus total ecosystem service values.
USDA Forest Service Proceedings RMRS-P-46CD. 2007. 604
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
programs throughout California, and once this information is coupled with
market-based value estimates, the total economic value can be estimated and
compared to treatment costs. The end result would provide the possibility
for a rigorous assessment of total social benefits associated with every BLM
fire treatment project implemented in California. In sum, the information in
this study effectively answers recent calls by policymakers to better account
for the full social costs and benefits associated with environmental programs
(National Research Council 2004). Armed with such information, it appears
that more informed decisions can be made in the future about protecting the
natural and built assets that matter most to the people in the wildland/urban
interface.
References
Argady, T.; Alder, J.; and others. 2005. Coastal systems and coastal communities.
Millennium ecosystem assessment: Conditions and trends. Washington, DC:
Island Press.
Bingham, G.; Bishop, R.C.; and others. 1995. Issues in ecosystem valuation:
Improving information for decision making. Ecological Economics 14: 73-90.
Costanza, R.; d’Arge, R.; and others. 1997. The value of the world’s ecosystem
services and natural capital. Nature 387: 253-260.
Daily, G.C. 1997. Nature’s services: Societal dependence on natural ecosystems.
Washington DC: Island Press.
Desvousges, W.H.; Johnson, F.R.; and others. 1998. Environmental policy analysis
with limited information: Principles and application of the transfer method.
Northampton, MA: Edward Elgar Publishing.
Downing, M.; Ozuna, T. 1996. Testing the reliability of the benefit function transfer
approach. Journal of Environmental Economics and Management 30: 316-322.
Environmental Protection Agency, U.S. (EPA). 2000. Guidelines for preparing
economic analyses. Washington, DC.
Everett, Y. 2002. Community participation in fire management planning: A case
from California, USA. Communities in Flames Proceedings of 1st International
Conference on Community Involvement in Fire Management. R AP Publication
2002/25. Bangkok, Thailand: United Nations, Food and Agricultural
Organization, Regional Office for Asia and the Pacific.
Farber, S. 1987. The value of coastal wetlands for protection of property against
hurricane wind damage. Journal of Environmental Economics and Management
14(2): 143-151.
Finney, M.A. 2001. Design of regular landscape fuel treatment patterns for modifying
fire behavior and growth. Forest Science 47: 219-228.
Fotheringham, A.S.; Brunsdon, C.; and others. 2000. Quantitative geography:
Perspectives on spatial data analysis publication. London, England: Sage.
Ganz, D.J.; Moore, P.F. 2002. Living with fire. Communities in Flames Proceedings
of 1st International Conference on Community Involvement in Fire Management.
R AP Publication 2002/25. Bangkok, Thailand: United Nations, Food and
Agricultural Organization, Regional Office for Asia and the Pacific.
Heal, G.M. 2004. Intertemporal welfare economics and the environment. Handbook
of environmental economics. K.G. Maler and J.Vincent. Amsterdam, North
Holland:Elsevier Publishers.
Heberlein, T.A.; Wilson, M.A.; and others. 2005. Rethinking the scope test as a
criterion for validity in contingent valuation. Journal of Environmental Economics
50(1): 1-22.
USDA Forest Service Proceedings RMRS-P-46CD. 2007.
605
Efficacy of the California Bureau of Land Management Community Assistance and ­Hazardous Fuels Programs
Ganz, Saah, Wilson, and Troy
Hodgson, R. 1994. Strategies for and barriers to public adoption of fire safe
behavior. The Biswell symposium: Fire issues and solutions in urban interface and
wildland ecosystems. General Technical Report GTR-PSW-158. Albany, CA: U.S.
Department of Agriculture, Forest Service, Pacific Southwest Research Station.
K irchhoff, S.; Colby, B.G.; and others. 1997. Evaluating the performance of
benefit transfer: An empirical inquiry. Journal of Environmental Economics and
Management 33(1): 75-93.
Knapp, E.E.; Stephens, S.L.; and others. 2004. Fire and fire surrogate study in
the Sierra Nevada: Evaluating restoration treatments at Blodgett Forest and
Sequoia National Park Proceedings of the Sierra Nevada Science Symposium;
2002 October 7-10, Kings Beach, CA, Gen. Tech. Rep. PSW-GTR-193. Albany,
CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research
Station. 287 p.
Loomis, J.B. 1992. The evolution of a more rigorous approach to benef it
transfer - benefit function transfer. Water Resources Research 28(3): 701-705.
Millennium Ecosystem Assessment. 2003. Ecosystems and human well-being: A
framework for assessment. Washington DC: Island Press.
National Research Council. 2004. Valuing ecosystem services: Toward better
environmental decision making. Washington, DC: National Academies Press.
National Wildfire Coordinating Group (NWCG). 2001. Review and update of the
1995 Federal wildland fire management policy. . Boise, ID: National Interagency
Fire Center. .
Openshaw, S.; Charlton, M.E.; and others. 1987. A mark i geographical analysis
machine for the automated analysis of point data sets. International Journal of
Geographical Information Systems 1: 359-377.
Pretty, J.N.; Brett, C.; and others. 2000. An assessment of the total external costs
of U.K. Agriculture. Agricultural Systems 65: 113-136.
Ricketts, T.H.; Daily, G.C.; and others. 2004. Economic value of tropical forest to
coffee production. Ecology 101(34).
Smith, V.K. 1992. On separating defensible benefit transfers from smoke and mirrors.
Water Resources Research 28(3): 685-694.
U.S. Department of Agriculture (USDA). 1995. Course to the future: Positioning fire
and aviation management. Washington, DC: USDA, Forest Service, Department
of Fire and Aviation Management.
U.S. Department of the Interior-U.S. Department of Agriculture (USDI–USDA).
1995. Federal wildland fire management and policy and program review. Boise,
ID: USDI, Bureau of Land Management.
Wilson, M.A.; Carpenter, S.R. 1999. Economic valuation of freshwater ecosystem
services in the United States 1971-1997. Ecological Applications 9(3): 772-783.
Wilson, M.A.; Troy, A. 2005. Accounting for ecosystem services in a spatially
explicit format: Value transfer and geographic information systems. International
Workshop on Benefits Transfer and Valuation Databases, Washington DC.
Wilson, M.A.; Troy, A.; and others. 2004. The economic geography of ecosystem
goods and services: Revealing the monetary value of landscapes through transfer
methods and geographic information systems. Cultural landscapes and land use.
M. Dietrich and V. D. Straaten. The Netherlands: Kluwer Academic Publishers.
Winter, G.; Fried, J.S. 2000. Homeowner perspectives on fire hazard, responsibility,
and management strategies at the wildland-urban interface. Society and Natural
Resources 13: 33-49.
USDA Forest Service Proceedings RMRS-P-46CD. 2007. 606